This section is intended to introduce various aspects of the art, which may be associated with embodiments of the disclosed techniques. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the disclosed techniques. Accordingly, this section should be read in this light, and not necessarily as an admission of prior art.
Over the past few decades, numerous technological advances in the oil industry have increased the success rate of finding reserves, developing these and improving the hydrocarbon recovery from existing resources. In addition, advances in computing capabilities have enabled geologists and engineers to model the reservoirs with increasing accuracy. Various technologies have been developed to understand a prospective reservoir by providing geological and reservoir information at different scales varying from a few inches (for example in core plug analysis) to tens of meters horizontally and a few meters vertically (seismic imaging data).
Construction of reservoir models has become a crucial step in resource development as reservoir modeling allows the integration of all available data in combination with a geologic model. One of the challenges in reservoir modeling is accurate representation of reservoir geometry, including the structural framework which may include major depositional surfaces that are nearly horizontal (also known as horizons), fault surfaces which can have arbitrary spatial size and orientation, and detailed stratigraphic layers. FIG. 1 illustrates a complex reservoir geometry which contains multiple fault surfaces which deviate from the vertical direction.
A structural framework outlines the major components of the reservoir and it is often used to model the fluid volumes located in the reservoir and the fluid movement during production. It is therefore helpful for the structural framework to be modeled accurately. However, to date, modeling of structural frameworks for practical reservoir modeling has been hampered by difficulties in generating a suitable grid. Specific challenges in generating a grid for a structural framework arise from the complex structure of sub-surface reservoir geometries. The typical aspect ratio of reservoir dimensions (horizontal in relation to vertical dimensions) can be several orders of magnitude. As a consequence, the aspect ratio of the grid cells is usually between 10 and 100.
Prismatic or 2.5 D Voronoi grids, constructed by the projection or extrusion of a 2D Voronoi grid in a vertical or near vertical direction, are widely accepted for reservoir simulations (see, for example, WO 2008/150325). The prismatic grid cells can be easily constrained to resolve horizons or stratigraphic layer boundaries. Voronoi grids are much more flexible and adaptive than structured corner point grids which are commonly used in reservoir simulators. Voronoi grids generally require fewer grid cells to represent and simulate the geometry in comparison to conventional corner point grids. This reduces computing power requirements whilst the accuracy of the models is not compromised. However, in complex reservoir geometries where fault surfaces deviate from the vertical plane, generating an accurate constrained grid still poses problems and as a result, the accuracy of reservoir models for complex reservoir geometries is still compromised.
“Efficient and accurate reservoir modeling using adaptive gridding with global scale up”, Branets et al., SPE 118946 (2009), discloses techniques for generating an adaptively constrained 2.5D Voronoi grid.
U.S. Pat. No. 6,106,561 discloses a simulation gridding method and apparatus including a structured area gridder adapted for use by a reservoir simulator. This disclosure is concerned with generating a 2.5D structured grid based on segmented coordinate lines. Coordinate lines are vertical or near vertical lines which approximate the fault surface geometry. An areal 2D grid is projected along the coordinate lines to form a 2.5D prismatic grid. This gridding method cannot cope with complex system of faults or highly-deviated (from vertical) faults, as this results in unacceptable grids with inside-out cells and vertices outside of the model domain. Also, structured grids generally require a lot of computing power for solving the reservoir model, and therefore, these grids are unsuitable for the simulation of large reservoirs comprising multiple structural faults.
“Challenges and technologies in reservoir modeling”, Branets et al., Communications in Computational Physics, Volume 6, Number 1, pages 1-23, discloses an overview of the technology in reservoir modeling, grid generation, grid adaptation and global scale-up methods to date.
Aspects disclosed herein aim to obviate or at least mitigate the above described problems and/or to provide improvements generally.